NDLI: Comparative study of band-power extraction techniques for Motor Imagery classification

Content Provider	IEEE Xplore Digital Library
Author	Brodu, N. Lotte, F. Lecuyer, A.
Copyright Year	2011
Description	Author affiliation: LTSI, University of Rennes 1, Campus de Beaulieu, Bât 22, 35042 Rennes Cedex - France (Brodu, N.) \|\| INRIA, Campus de Beaulieu, Avenue du Général Leclerc, 35042 Rennes Cedex - France (Lecuyer, A.) \|\| Institute for Infocomm Research (I2R), Signal Processing Department, Brain-Computer Interface Laboratory, 1 Fusionopolis way, 138632, Singapore (Lotte, F.)
Abstract	We review different techniques for extracting the power information contained in frequency bands in the context of electroencephalography (EEG) based Brain-Computer Interfaces (BCI). In this domain it is common to apply only one algorithm for extracting the power information. However previous work and our current study confirm that one may indeed expect varying degrees of success by choosing inadequate algorithms for the power extraction. Our results suggest that on average one algorithm seems superior for extracting the power information for Motor Imagery tasks : the application of a Morlet wavelet on the raw EEG signals, with the time-frequency resolution tradeoff selected by cross-validation.
Starting Page	1
Ending Page	6
File Size	210298
Page Count	6
File Format	PDF
ISBN	9781424498901
e-ISBN	9781424498918
DOI	10.1109/CCMB.2011.5952105
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-04-11
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accuracy Estimation Time frequency analysis Feature extraction Data mining Spectrogram Brain computer interfaces
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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Comparative study of band-power extraction techniques for motor imagery classification (2011).

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Subject-specific channel selection for classification of motor imagery electroencephalographic data

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Classification of Motor Imagery EEG Signals Based on STFTs

Comparative study of band-power extraction techniques for Motor Imagery classification

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